Intuition

Course video 34 of 54

We spent 3 previous modules working on the value-based methods: learning state values, action values and whatnot. Now's the time to see an alternative approach that doesn't require you to predict all future rewards to learn something.

Welcome to the Reinforcement Learning course.
Here you will find out about:
- foundations of RL methods: value/policy iteration, q-learning, policy gradient, etc.
--- with math & batteries included
- using deep neural networks for RL tasks
--- also known as "the hype train"
- state of the art RL algorithms
--- and how to apply duct tape to them for practical problems.
- and, of course, teaching your neural network to play games
--- because that's what everyone thinks RL is about. We'll also use it for seq2seq and contextual bandits.
Jump in. It's gonna be fun!